Latest Thoughts on Strategy & Technology
Practical insights on AI, strategy execution, technology adoption, and organizational change in modern construction.
Closing the loop between estimates and actuals requires a deliberate mapping between estimating assumptions and delivery outcomes. This mapping is rarely available by default because the two activities operate in different systems with different purposes.
AI doesn't eliminate the need for estimating expertise. It provides tools that let estimators work at higher levels of abstraction, focusing on what matters: defining relevant drivers, understanding context, translating uncertainty into decision support, rather than fighting data quality issues or manually tracking hundreds of marginal correlations.
Toil - you’re not making key decisions or doing deep work, you’re executing a process to keep ‘the machine’ running.
Automation is often discussed as though it were a single capability. In practice, it refers to several distinct system architectures that differ in what they control, how decisions are made, and where responsibility sits.
Parametric estimation has proven benefits for certain project types. It enables owners and builders to generate quick, accurate estimates, make faster decisions, and compare alternatives with ease.
The real opportunity is to design shared rules, thresholds, and workflows that allow routine coordination to happen without constant escalation.
Generic AI will not be enough. You cannot simply buy it and expect it to fit. You will need to craft something that reflects your organisation, your constraints, and your ambitions, because every company is different, and should be.
Light AI governance is not an added layer of process. It is simply the operational expression of observability and evals. It reassures the organisation that new capabilities are being introduced with equal attention to reliability.
Early-stage estimating has always depended on a rather small circle of people who possess the rare ability to convert half-formed concepts into plausible numbers.
Agentic AI offers a credible way out of the paper chase loop.
When I think about how we should approach Agentic AI, I often come back to the analogy of mentoring a new intern. The comparison may sound lighthearted, but it holds remarkably well. An intern arrives full of potential and enthusiasm, yet without much experience in how things actually get done.
Builders tend to trust what they can see and feel. For many, AI still feels abstract, more a concept than a craft. The AI Mentorship & Skills Development Program was built to bridge that gap.
The New Construction Leadership Challenge - Leading Smart, Tech-Savvy Teams Through the AI Era. Learn how to balance curiosity with accountability and create frameworks for responsible AI experimentation.
Exploring how to unlock creativity and diversity in LLM outputs using verbalized sampling techniques—sometimes you need controlled chaos.
How alignment charts can help leaders think about AI governance, workflows, and building reliable agentic systems.
Thanks to ICBA and Sanjeev Dhillon for hosting an excellent event last week
We are incredibly excited to welcome Bill Dall to the Cypress Falls team as co-founder and CTO.
Bill recently attended the Vancouver Microsoft 365 Summit.
AI Opportunities in a Design-Bid-Build Workflow
AI Opportunities in a General Contractor Workflow
We were incredibly lucky to host ICML 2025 last week in Vancouver, and I'm struck by how we're seeing remarkable practical progress—new agent frameworks are maturing rapidly, Small Language Models are delivering real business value, and companies are successfully deploying AI at scale.
Despite billions poured into AI, only 25% of Fortune 500 projects hit their ROI target—data challenges are one of the biggest hurdles. Learn why perfect data is a myth and how to approach data challenges effectively.
Learn the three critical pillars that separate successful technology transformations from expensive failures, based on real experience scaling from 4 to 150+ people.
Exploring why SOPs often fail to deliver expected efficiency gains and how AI agents can help bridge the gap between theoretical processes and practical execution.
Harness the power of technology and AI as a competitive advantage.